Cloud Data Engineering Specialist

2 days ago

Bacoor, Calabarzon, Philippines beBeeDataEngineering Full time ₱5,000,000 - ₱8,000,000
Cloud Data Engineering Specialist

We are seeking a highly skilled Cloud Data Engineering Specialist to join our team.

This role involves designing, building, and maintaining scalable data pipelines using cloud-based services such as AWS.

Key Responsibilities
  • Data Infrastructure Development: Design and develop efficient data pipelines using cloud services like S3, Glue, Lambda, and RDS.
  • ETL Process Development: Build robust ETL processes to ingest, transform, and store data efficiently.
  • Database Optimization: Manage and optimize relational databases to support business needs.
  • Data Quality and Governance: Ensure high-quality data through validation, monitoring, and governance best practices.
  • Automation and Scripting: Develop scripts and automation tools (Python, SQL, Bash) to streamline data processes and workflows.
  • Data Accessibility: Support business users by ensuring data is structured and accessible in reporting tools like Tableau or Metabase.
  • DevOps and CI/CD: Implement best practices for version control, testing, and deployment of data pipelines (Terraform, GitHub Actions, etc.).
Requirements
  • Cloud-Based Data Platforms: Proven experience in data engineering, working with cloud-based data platforms (AWS).
  • Python and SQL Proficiency: Strong proficiency in Python for data processing and automation, and experience with SQL and database management (PostgreSQL, MySQL, or similar).
  • AWS Services Experience: Hands-on experience with AWS services such as Glue, S3, Lambda, and RDS.
  • ETL Best Practices: Understanding of ETL/ELT best practices and experience building data pipelines.
  • Data Visualization: Experience with data visualisation and BI tools such as Tableau or Metabase.
  • Infrastructure Automation: Experience with infrastructure-as-code tools (Terraform, CloudFormation) for data infrastructure automation.
Desirable Skills
  • ML Technologies: Familiarity with ML technologies (Sagemaker).
  • Agile Environments: Experience working in Agile environments and familiarity with tools like Jira and Confluence.
  • CI/CD for Data Workflows: Knowledge of CI/CD for data workflows and version control using Git.

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